Remote Sensing-based Yield Curves (RSYC) for Canada’s Forested Ecozones
National Forest Carbon Monitoring, Accounting and Reporting System (NFCMARS) is designed to:
estimate past changes in forest carbon stocks, such as from 1990 to the present (monitoring)
predict changes in carbon stocks, based on scenarios of future disturbance rates and management actions, in the next 2 to 3 decades (projection)
spatial extent (single jurisdiction, Canada-wide)
developed for the dominant (most common) species only
developed for managed forests
often based on a limited number of samples
Entire Canada (all treed pixels)
Species-specific (not only most common tree species)
Consistent methodology
Locally representative
Fine level of spatial detail
Designed to work with RS data
Model form after (Fortin and Lavoie 2022):
\[ AGB = \beta_1 e^{-\beta_4 age} (1 - e^{-\beta_2 age})^{\beta_3} \]
NLME:
National AGB yield curves (N=1892)
Multi-species:
Species-specific:
Yield curves represent the average AGB in the tile
Evaluation – compare mean AGBRSYC with AGBREF by 20 year age classes
MAGPlot data:
Over 50k plots, harmonized dataset
Independent
Mix of different sampling designs
Raking ratio: weights (per plot) to adjust for under- or over-representation of different forest strata (e.g. plots located in more productive stands)
Publications (open access):
Tompalski, P., Hermosilla, T., Baral, S.K., Wulder, M.A., White, J.C. 2025. National remote sensing-derived aboveground biomass yield curves for Canada. Forestry: An International Journal Of Forest Research. https://doi.org/10.1093/forestry/cpaf067
Tompalski, P., Wulder, M.A., White, J.C., Hermosilla, T., Riofrío, J., Kurz, W.A., 2024. Developing aboveground biomass yield curves for dominant boreal tree species from time series remote sensing data. Forest Ecology and Management 561, 121894. https://doi.org/10.1016/j.foreco.2024.121894
R package: https://ptompalski.github.io/RSYC
This presentation: https://ptompalski.github.io/RSYC_overview/
Remote Sensing-based Yield Curves | piotr.tompalski@nrcan-rncan.gc.ca